Human Papillomavirus Infection in Female Sex Workers: A Case Control Study
Bibliographic record
Abstract
BACKGROUND: To determine the association of infection with human papillomavirus (HPV) and the occupation of female sex worker; and the correlation of infection with HPV with sociodemographic, clinical and behavioral characteristics of female sex workers. METHODS: We performed a case-control study of 217 female sex workers and 354 women without sex work in Durango City, Mexico. We determined the prevalence of infection with HPV in cervical samples of women using polymerase chain reaction, and HPV genotypes were determined using line probe assay. Bivariate and multivariate analyses were used to assess the association between the characteristics of women and infection. RESULTS: Twelve (5.5%) of the 217 sex workers, and 10 (2.8%) of the 354 control women were positive for HPV DNA (age-adjusted OR = 1.51; 95% CI: 0.62 - 3.68; P = 0.36). Six (50.0%) of the 12 HPV DNA positive sex workers had infections with high-risk genotypes (16, 31, 33, 35, 51, 58). Seven (70%) of the 10 HPV DNA positive control women had infections with high-risk genotypes (16, 18, 56, 58, and 66). The frequency of high risk genotypes in the control women was equal with that found in the female sex workers (P = 0.41). Logistic regression analysis showed that the variable alcohol consumption was associated with HPV infection (OR = 4.0; 95% CI: 1.0 - 16.0; P = 0.04). CONCLUSIONS: No association between HPV infection and female sex work was found in our setting. High risk HPV genotypes were prevalent among the women studied. Results can be used for the design of preventive measures against HPV infection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".